Supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized LMPU test”

This document contains supplemental material for the paper [2]. The notations in this document are the same as in [2]. In particular, we first present here the proof of Theorem 1 in [2]. This theorem expresses the locally most powerful unbiased (LMPU) test, which is a general method for local detect...

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Autores principales: Levy, Eyal, Routtenberg, Tirza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7829148/
https://www.ncbi.nlm.nih.gov/pubmed/33532522
http://dx.doi.org/10.1016/j.dib.2020.106714
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author Levy, Eyal
Routtenberg, Tirza
author_facet Levy, Eyal
Routtenberg, Tirza
author_sort Levy, Eyal
collection PubMed
description This document contains supplemental material for the paper [2]. The notations in this document are the same as in [2]. In particular, we first present here the proof of Theorem 1 in [2]. This theorem expresses the locally most powerful unbiased (LMPU) test, which is a general method for local detection, in the presence of known nuisance parameters. Second, we present here the Matlab code of the LMPU and the generalized LMPU for the special case of detection of a small deviation in the frequency of sinusoidal signals, which arises in various signal processing applications.
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spelling pubmed-78291482021-02-01 Supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized LMPU test” Levy, Eyal Routtenberg, Tirza Data Brief Data Article This document contains supplemental material for the paper [2]. The notations in this document are the same as in [2]. In particular, we first present here the proof of Theorem 1 in [2]. This theorem expresses the locally most powerful unbiased (LMPU) test, which is a general method for local detection, in the presence of known nuisance parameters. Second, we present here the Matlab code of the LMPU and the generalized LMPU for the special case of detection of a small deviation in the frequency of sinusoidal signals, which arises in various signal processing applications. Elsevier 2021-01-08 /pmc/articles/PMC7829148/ /pubmed/33532522 http://dx.doi.org/10.1016/j.dib.2020.106714 Text en © 2021 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Levy, Eyal
Routtenberg, Tirza
Supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized LMPU test”
title Supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized LMPU test”
title_full Supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized LMPU test”
title_fullStr Supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized LMPU test”
title_full_unstemmed Supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized LMPU test”
title_short Supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized LMPU test”
title_sort supplemental data for the paper “low-complexity detection of small frequency deviations by the generalized lmpu test”
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7829148/
https://www.ncbi.nlm.nih.gov/pubmed/33532522
http://dx.doi.org/10.1016/j.dib.2020.106714
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